| Convolutional LSTM network: A machine learning approach for precipitation nowcasting X Shi, Z Chen, H Wang, DY Yeung, WK Wong, W Woo Advances in neural information processing systems 28, 2015 | 5790 | 2015 |
| Deep learning for precipitation nowcasting: A benchmark and a new model X Shi, Z Gao, L Lausen, H Wang, DY Yeung, W Wong, W Woo Advances in neural information processing systems 30, 2017 | 457 | 2017 |
| Gaan: Gated attention networks for learning on large and spatiotemporal graphs J Zhang, X Shi, J Xie, H Ma, I King, DY Yeung arXiv preprint arXiv:1803.07294, 2018 | 427 | 2018 |
| Dynamic key-value memory networks for knowledge tracing J Zhang, X Shi, I King, DY Yeung Proceedings of the 26th international conference on World Wide Web, 765-774, 2017 | 332 | 2017 |
| Spatiotemporal modeling for crowd counting in videos F Xiong, X Shi, DY Yeung Proceedings of the IEEE international conference on computer vision, 5151-5159, 2017 | 172 | 2017 |
| Relational stacked denoising autoencoder for tag recommendation H Wang, X Shi, DY Yeung Twenty-ninth AAAI conference on artificial intelligence, 2015 | 143 | 2015 |
| GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. J Guo, H He, T He, L Lausen, M Li, H Lin, X Shi, C Wang, J Xie, S Zha, ... J. Mach. Learn. Res. 21 (23), 1-7, 2020 | 142 | 2020 |
| Star-gcn: Stacked and reconstructed graph convolutional networks for recommender systems J Zhang, X Shi, S Zhao, I King arXiv preprint arXiv:1905.13129, 2019 | 117 | 2019 |
| Collaborative recurrent autoencoder: Recommend while learning to fill in the blanks H Wang, X Shi, DY Yeung Advances in Neural Information Processing Systems 29, 2016 | 112 | 2016 |
| Machine learning for spatiotemporal sequence forecasting: A survey X Shi, DY Yeung arXiv preprint arXiv:1808.06865, 2018 | 79 | 2018 |
| Relational deep learning: A deep latent variable model for link prediction H Wang, X Shi, DY Yeung Thirty-first AAAI conference on artificial intelligence, 2017 | 61 | 2017 |
| Natural-parameter networks: A class of probabilistic neural networks H Wang, X Shi, DY Yeung Advances in neural information processing systems 29, 2016 | 54 | 2016 |
| Distributed stochastic ADMM for matrix factorization ZQ Yu, XJ Shi, L Yan, WJ Li Proceedings of the 23rd ACM International Conference on Conference on …, 2014 | 27 | 2014 |
| Symbolic music generation with transformer-gans A Muhamed, L Li, X Shi, S Yaddanapudi, W Chi, D Jackson, R Suresh, ... Proceedings of the AAAI Conference on Artificial Intelligence 35 (1), 408-417, 2021 | 17 | 2021 |
| Visual speaker identification and authentication by joint spatiotemporal sparse coding and hierarchical pooling JY Lai, SL Wang, AWC Liew, XJ Shi Information Sciences 373, 219-232, 2016 | 15 | 2016 |
| Benchmarking multimodal automl for tabular data with text fields X Shi, J Mueller, N Erickson, M Li, AJ Smola arXiv preprint arXiv:2111.02705, 2021 | 10 | 2021 |
| Multimodal automl on structured tables with text fields X Shi, J Mueller, N Erickson, M Li, A Smola 8th ICML Workshop on Automated Machine Learning (AutoML), 2021 | 7 | 2021 |
| A deep-learning method for precipitation nowcasting W Wong, X Shi, DY Yeung, WC Woo WMO WWRP 4th International Symposium on Nowcasting and Veryshort-range …, 2016 | 6 | 2016 |
| Deep learning and the weather forecasting problem: Precipitation nowcasting Z Gao, X Shi, H Wang, DY Yeung, W Woo, WK Wong Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote …, 2021 | 5 | 2021 |
| Lorien: Efficient deep learning workloads delivery CH Yu, X Shi, H Shen, Z Chen, M Li, Y Wang Proceedings of the ACM Symposium on Cloud Computing, 18-32, 2021 | 4 | 2021 |
Dit-Yan YeungChair Professor, Department of CSE, HKUST, Hong KongVerified email at cse.ust.hk
